Deakin University
Browse

File(s) under permanent embargo

Prosthetic motor imaginary task classification based on EEG quality assessment features

Version 2 2024-06-03, 14:31
Version 1 2016-03-23, 15:10
conference contribution
posted on 2024-06-03, 14:31 authored by S Haggag, Shady MohamedShady Mohamed, O Haggag, S Nahavandi
Brain Computer Interface (BCI) plays an important role in the communication between human and machines. This communication is based on the human brain signals. In these systems, users use their brain instead of the limbs or body movements to do tasks. The brain signals are analyzed and translated into commands to control any communication devices, robots or computers. In this paper, the aim was to enhance the performance of a brain computer interface (BCI) systems through better prosthetic motor imaginary tasks classification. The challenging part is to use only a single channel of electroencephalography (EEG). Arm movement imagination is the task of the user, where (s)he was asked to imagine moving his arm up or down. Our system detected the imagination based on the input brain signal. Some EEG quality features were extracted from the brain signal, and the Decision Tree was used to classify the participant's imagination based on the extracted features. Our system is online which means that it can give the decision as soon as the signal is given to the system (takes only 20 ms). Also, only one EEG channel is used for classification which reduces the complexity of the system which leads to fast performance. Hundred signals were used for testing, on average 97.4% of the up-down prosthetic motor imaginary tasks were detected correctly. This method can be used in many different applications such as: moving artificial limbs and wheelchairs due to it's high speed and accuracy.

History

Volume

9492

Pagination

87-94

Location

Istanbul, Turkey

Start date

2015-11-09

End date

2015-11-12

ISSN

0302-9743

eISSN

1611-3349

ISBN-13

9783319265605

Language

eng

Publication classification

E Conference publication, E1 Full written paper - refereed

Copyright notice

2015, Springer

Title of proceedings

ICONIP 2015 : Neural information processing : 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015 : proceedings

Event

Neural Information Processing. Conference (22nd : 2015 : Istanbul, Turkey)

Publisher

Springer

Place of publication

New York, N.Y.

Series

Lecture Notes in Computer Science

Usage metrics

    Research Publications

    Categories

    No categories selected

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC